code: def resolve_sentence(self, sentence):
      tokens, is_word_start = self.tokenize_sentence(sentence)
  
      token_ids = self.tokenizer.convert_tokens_to_ids(tokens)
      to_input = np.pad(
          token_ids,
          [(0, self.max_length - len(token_ids))],
          mode="constant",
      )
      to_input = to_input.reshape((1, self.max_length))
  
      embeddings = self.session.run(
          self.embeddings_op, feed_dict={self.token_ids_op: to_input}
      )
      embeddings = np.squeeze(embeddings)
      embeddings = embeddings[: len(token_ids), :]
  
      return TokenEmbeddings.create_sentence(
          tokens, is_word_start, embeddings
      )
  
imports: import shutil
  import numpy
  import plyvel
  import os.path
  import sys
  from bert.modeling import *
  from bert.tokenization import *
  import json
  import os.path
  import numpy
label_desc: Use image node_id 4 for calling the BertEmbeddingsResolver obj's underlying member method code with example usage: obj.resolve_sentence(sentence) and returns: TokenEmbeddings